Most cameras used by professional photographers and amateurs alike suffer from flare light, i.e., non-image forming light superimposed on the image forming light. Camera designers often incorporate baffles to attenuate the magnitude of flare light due to off axis stray light sources. However, no set of baffles can completely eliminate flare light. Another component of flare light is derived from scattered light off the optical elements of the camera. For example, dirt or fingerprints on a lens surface can scatter light that would otherwise be image forming light. The scattered light contributes to the overall flare light. Flare light affects images by reducing the dynamic range of the intensities of light recorded and also has the effect of de-saturating colored objects. Images produced with cameras that produce high intensity levels of flare light appear low in contrast.
In U.S. Pat. No. 4,974,810, Fiske discloses an optical imaging system designed to compensate for the effects of flare light. The system disclosed by Fiske includes a detector for detecting light from an image and producing a signal related to the amount of light detected, a flare light detector for viewing the flare light and producing a signal related to the amount of light viewed, and a compensating device for reducing the signal from the image detector in response to the signal from the flare light detector. In this system, the amount of flare light is monitored by a separate electronic sensor while the image forming light is recorded by an area electronic imaging sensor. The flare light component, as approximated by the signal produced by the separate electronic sensor, is subtracted from the signal produced by the area electronic imaging sensor, thus compensating the image for the effects of flare light. The flare compensation method disclosed by Fiske relies on the simultaneous measurement of image forming light and non-image forming light.
A flare compensation method is disclosed by Omura in U.S. Pat. No. 5,208,874. The method includes the following steps of: optically scanning a reference image irradiated by a light source, the scanning system outputting reference image information corresponding to the reference image; generating a function denoting a response with respect to the deterioration of the image information caused by the flare based on the reference image information obtained by the scanning system; optically scanning a document irradiated by the light source by the scanning system; and performing a de-convolution operation in which the image information obtained by the scanning system and the above function are used. The method disclosed by Omura also makes explicit use of measuring the flare light distribution of a specific device and as such is not applicable for processing digital images from different devices.
The average luminance intensity level of scanned film images (obtained by scanning motion picture film frames) often undesirably varies from frame to frame due to optical scatter in the lens assembly of the scanning video camera. Some systems for converting motion picture film into video have implemented “flare correction” algorithms to smooth undesired luminance variation between consecutive frames. In U.S. Pat. No. 5,155,586, Levy et al. discloses a system that digitally generates flare correction factor signals, and employs the flare correction factor signals to compensate for undesired luminance variations from frame to frame. These “flare correction” methods employed by video systems are not designed to remove the effects of flare light introduced by the optical camera.
A video camera system designed to compensate for the effects of flare light is disclosed by Nakamura in U.S. Pat. No. 5,280,354. The video camera disclosed by Nakamura is equipped with an image sensor for producing an analog video signal, an A-D converter for converting the analog video signal into a digital video signal in a manner that any component thereof above a predetermined luminance level is clipped, and a flare correcting circuit for removing any flare component superposed on the digital video signal. Nakamura's method calculates a flare compensation signal that depends on both the average luminance level detected during a time period of several fields of the digital video signal and the detected time period during which the analog signal is clipped relating to a brightly lit object. The flare compensation signal is subtracted from the digital video signal.
An example of an image processing method that incorporates an image dependent image processing model designed to remove the effects of flare light is disclosed by Namizuka et al. in U.S. Pat. No. 5,892,852. Namizuka's method includes a processing step that calculates a flare light level based on sensing image pixels below a predetermined threshold value. The calculated flare light level is subtracted from the image data in a later processing step. In the method disclosed by Namizuka et al., the flare removal step is only applied to pixel data identified as relating to image regions containing character data since the flare removal step is designed to produce binary processed pixels values. Thus the “flare” component described by Namizuka et al. relates more to a desired “black level” for imaged character data than to overall flare light caused by the optical system since flare compensation is not performed for continuous tone image regions which experience the same overall flare light.
In U.S. Pat. No. 6,229,624, Gilman et al. disclose a method of compensating for the effects of system flare light through the use of a tone scale function. In this method, an aim tone scale function, or curve, is selected from a family of aim curves for a desired output medium having a predetermined maximum density. Each of the curves in the family of curves is constructed in such a manner such that the slope of the curve relating to the contrast of dark image regions is greater for darker image regions. Thus the application of the selected aim curve when applied to digital images has a similar effect of compensating for flare light introduced either by the image capture device or the printing device. The selection of the aim curve in the method disclosed by Gilman et al. is a manual operation, i.e., the user must the select the aim curve to be used in the image processing.
Multispectral remote sensing systems record images in many different spectral wavelength bands. Atmospheric haze due to light scattering can cause the sensed images to have elevated scene reflectance values. The magnitude of this effect is dependent on the wavelength of light with the effect being of greater magnitude for shorter wavelengths. Thus the multiple bands of a multispectral remote sensing system are affected by atmospheric haze to a varying degree.
In the journal article “An Improved Dark-Object Subtraction Technique for Atmospheric Scattering Correction of Multispectral Data”, Remote Sensing of the Environment, 1988, 24, 459-479, Chavez describes a digital image processing method for removing the affects of atmospheric haze. In this method a pixel value corresponding to a dark object is selected in one band of a multispectral image usually corresponding to a long wavelength of light. Suitable dark objects are pools of water sensed in a infra-red wavelength band, since infra-red wavelength bands are known to be affected by little or no atmospheric haze and water has a known reflectance in the infra-red. A relative scattering model (which accounts for the relative magnitude of atmospheric haze as a function of wavelength) is used to calculate a pixel offset for each of the other multispectral bands. The pixel offsets are subtracted from the image pixel data for their respective multispectral bands. The resulting processed images have the effects of atmospheric haze removed, restoring the radiometry of the multispectral image. The linear subtraction mathematics used to remove atmospheric haze are the same as needed for a flare light removal algorithm for flare light in visible wavelength imaging systems. However, the method described by Chavez cannot be applied directly to remove flare light for visible wavelength optical camera systems since most natural images do not contain ideal dark-objects corresponding to a no-flare condition.
What is needed is a digital image processing method that can automatically sense the amount of flare light from the pixels of a digital image without having to rely on a reference dark-object or sense the non-imaged flare light within the original camera and compensate the image for the sensed amount of flare light.